Click to open the HelpDesk interface
AECE - Front page banner



JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Nov 2018
Next issue: Feb 2019
Avg review time: 81 days


Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


2,140,349 unique visits
Since November 1, 2009

Robots online now


SCImago Journal & Country Rank

SEARCH ENGINES - Google Pagerank


Anycast DNS Hosting

 Volume 18 (2018)
     »   Issue 4 / 2018
     »   Issue 3 / 2018
     »   Issue 2 / 2018
     »   Issue 1 / 2018
 Volume 17 (2017)
     »   Issue 4 / 2017
     »   Issue 3 / 2017
     »   Issue 2 / 2017
     »   Issue 1 / 2017
 Volume 16 (2016)
     »   Issue 4 / 2016
     »   Issue 3 / 2016
     »   Issue 2 / 2016
     »   Issue 1 / 2016
 Volume 15 (2015)
     »   Issue 4 / 2015
     »   Issue 3 / 2015
     »   Issue 2 / 2015
     »   Issue 1 / 2015
  View all issues  


Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


  2/2009 - 7

Improving Power System Risk Evaluation Method Using Monte Carlo Simulation and Gaussian Mixture Method

MOUSAVI, O. A. See more information about MOUSAVI, O. A. on SCOPUS See more information about MOUSAVI, O. A. on IEEExplore See more information about MOUSAVI, O. A. on Web of Science, FARASHBASHI-ASTANEH, M. S. See more information about  FARASHBASHI-ASTANEH, M. S. on SCOPUS See more information about  FARASHBASHI-ASTANEH, M. S. on SCOPUS See more information about FARASHBASHI-ASTANEH, M. S. on Web of Science, GHAREHPETIAN, G. B. See more information about GHAREHPETIAN, G. B. on SCOPUS See more information about GHAREHPETIAN, G. B. on SCOPUS See more information about GHAREHPETIAN, G. B. on Web of Science
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (628 KB) | Citation | Downloads: 1,267 | Views: 4,868

Author keywords
Monte Carlo Simulation, Gaussian Mixture Method, linear programming, DC load flow, probability density function

References keywords
power(18), systems(12), system(10), dobson(8), failure(7), cascading(7), model(6), blackouts(6), reliability(5), methods(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2009-06-02
Volume 9, Issue 2, Year 2009, On page(s): 38 - 44
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.02007
Web of Science Accession Number: 000268723600007
SCOPUS ID: 70349167393

Quick view
Full text preview
The analysis of the risk of partial and total blackouts has a crucial role to determine safe limits in power system design, operation and upgrade. Due to huge cost of blackouts, it is very important to improve risk assessment methods. In this paper, Monte Carlo simulation (MCS) was used to analyze the risk and Gaussian Mixture Method (GMM) has been used to estimate the probability density function (PDF) of the load curtailment, in order to improve the power system risk assessment method. In this improved method, PDF and a suggested index have been used to analyze the risk of loss of load. The effect of considering the number of generation units of power plants in the risk analysis has been studied too. The improved risk assessment method has been applied to IEEE 118 bus and the network of Khorasan Regional Electric Company (KREC) and the PDF of the load curtailment has been determined for both systems. The effect of various network loadings, transmission unavailability, transmission capacity and generation unavailability conditions on blackout risk has been investigated too.

References | Cited By  «-- Click to see who has cited this paper

[1] A. Stefanini, A. Servida, S. Puppin, "Electric System Vulnerabilities: the Crucial Role of Information & Communication Technologies in Recent Blackouts", ELECTRA magazine, December 2005.

[2] Mario A. Rios, Daniel S. Kirschen, Dilan Jayaweera, Dusko P. Nedic and Ron N. Allan, "Value of Security: Modeling Time-Dependent Phenomena and Weather Conditions", IEEE Transactions on Power Systems, Vol. 17, No. 3, August 2002
[CrossRef] [Web of Science Times Cited 111] [SCOPUS Times Cited 157]

[3] W. Li, "Risk Assessment of power systems, Models, Methods, and applications", IEEE Press, John Wiley & Sons Inc. Publication, 2005.

[4] S. Deng, S. Meliopoulos, T. Mount, H. Sun, F. Yang, G. Stefopoulos, X. Cai, J. Ju, Y. Lee, "Modeling Market Signals for Transmission Adequacy Issues: Valuation of Transmission Facilities and Load Participation Contracts in Restructured Electric Power Systems", PSERC Publication, February 2007.

[5] F. Yang, A. P. S. Meliopoulos, G. J. Cokkinides, G. Stefopoulos, "A bulk power system reliability assessment methodology", International Conference on Probabilistic Methods Applied to Power Systems, Sept. 2004.

[6] B. A. Carreras, V. E. Lynch, I. Dobson, D. E. Newman, "Critical Points and Transitions in an Electric Power Transmission Model for Cascading Failure Blackouts", Choas, Vol. 12, Number 4, December 2002.

[7] D. S. Kirschen, D. Jayaweera, D. P. Nedic, R. N. Allan, "A Probabilistic Indicator of System Stress", IEEE Transactions on Power Systems, Vol. 19, No. 3, August 2004
[CrossRef] [Web of Science Times Cited 102] [SCOPUS Times Cited 131]

[8] I. Dobson, B. A. Carreras, V. E. Lynch, B. Nkei, D. E. Newman, "Estimating Failure Propagation in Models of Cascading Blackouts", 8th International Conference on Probability Methods Applied to Power Systems, September 2004.

[9] K. R. Wierzbicki, I. Dobson, "An Approach to Statistical Estimation of Cascading Failure Propagation in Blackouts", Third International Conference on Critical Infrastructure, September 2006.

[10] R. Billinton, R. N. Alen, "Reliability evaluation of engineering systems, Concepts and Techniques", Plenum Press, New York and London, 1983.

[11] R. Billinton, R. N. Alen, "Reliability Evaluation of Power Systems", Plenum Press, 1984.

[12] J. Chen, J. S. Thorp, I. Dobson, "Cascading Dynamics and Mitigation Assessment in Power System Disturbances via a Hidden Failure Model", Electrical Power and Energy Systems, 2004.

[13] A. Chakrabarti, S. Halder, "Power System Analysis Operation and Control", Prenice-Hall of India, New Delhi-110001, 2006.

[14] A. K. Jana, P. B. Dutta Gupta, G. Durgaprasad, "Hybrid Method to Determine Bus Voltage and Angle for Line Outage Contingency Evaluation", IEE Proceedings-C, Vol. 193, No. 3, 1992.

[15] J. Mitra, C. Singh, "Incorporating the DC Load Flow Model in the Decomposition-Simulation Method of Multi-Area Reliability Evaluation", IEEE Transactions on Power Systems, Vol. 11, No. 3, 1996
[CrossRef] [Web of Science Times Cited 38] [SCOPUS Times Cited 56]

[16] A. G. Bakirtzis, P. N. Biskas, "Decentralised DC Load Flow and Applications to Transmission Management", IEE Proc.Genev. Transm. And Distrib., Vol. 149., No.5, 2002.

[17] I. Skokljev, V. Maksimovic, "Congestion Management Utilizing Concentric Relaxation", Serbia Journal of Electrical Engineering, 2007.

[18] I. Dobson, B. A. Carreras, V. E. Lynch, D. E. Newman, "An Initial Model for Complex Dynamics in Electric Power System Blackouts", Hawaii International Conference on System Sciences, IEEE, January 2001

[19] Archambeau, C., Valle, M., Assenza, A., Verleysen, M., "Assessment of Probability Density Estimation Methods: Parzen Window and Finite Gaussian Mixtures", International Symposium on Circuits and Systems 2006: pp 3245- 3248

[20] Dusko P.Nedic, Ian Dobson, Daniel S. Kirschen, Benjamin A. Carreras, Vickie E. Lynch, "Criticality in Cascading Failure Blackout Model", 15th Power System Computational Conference, August 2005.

[21] Ian Dobson, Benjamin A. Carreras, Vickie E. Lynch, David E. Newman, "Complex System Analysis of Series of Blackouts: Cascading Failure, Criticality, and Self-organization", Bulk Power System Dynamics and Control-VI, 22-27 Aug, 2004.

[22] Ian Dobson, "Where is the Edge for Cascading Failure?: Challenges and Opportunities for Quantifying Blackout Risk", IEEE Power Engineering Society General Meeting, June 2007.

[23] C. Archambeau, M. Verleysen, "Fully Nonparametric Probability Density Function Estimation with Finite Gaussian Mixture Methods", 5th International Conference on Advances in Pattern Recognition Calcultta, Dec 2003, pp.81-84 .

[24] Pekka Paalanen, "Bayesian Classification Using Gaussian Mixture Model and EM Estimation: Implementations and Comparisons", Information Technology Project, Lappeenranta University of Technology, Department of Information Technology, 2004.

[25] W. Abd-Almageed, L. S. Davis, "Density Estimation Using Mixtures of Mixtures of Gaussians", Springer, Computer vision, Vol. 3954, ECCV 2006, pp: 410-422
[CrossRef] [SCOPUS Times Cited 9]

[26] R. Billinton, R. N. Alen, "Reliability Assessment of Large Electric Power Systems", Kluwer Academic Publishers, 1988 [PermaLink]

References Weight

Web of Science® Citations for all references: 251 TCR
SCOPUS® Citations for all references: 353 TCR

Web of Science® Average Citations per reference: 10 ACR
SCOPUS® Average Citations per reference: 14 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-01-15 11:19 in 47 seconds.

Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2019
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.

Website loading speed and performance optimization powered by: